Summary
Serina Chang is an Assistant Professor jointly appointed in EECS and Computational Precision Health at UC Berkeley and a member of BAIR, where she builds AI models that illuminate and improve human behavior and decision-making, especially for public health. Her work bridges rigorous machine learning, human-AI interaction, and computational social science, and has earned top honors including the KDD Dissertation and Best Paper Awards, a Google Research Scholar Award, and NSF and Meta fellowships. Trained at Stanford (PhD) and a former Microsoft Research postdoc, she combines production-facing engineering experience from internships at Google with academic depth in graph and social network methods. Notably, her research has influenced public discourse—featured by major outlets like The New York Times—reflecting a rare mix of methodological innovation and societal impact.
10 years of coding experience
1 year of employment as a software developer
Hunter College High School
Piano Violin Chamber music, Piano Violin Chamber music at Manhattan School of Music
Bachelor’s Degree Computer Science Sociology, Bachelor’s Degree Computer Science Sociology at Columbia University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Stanford University
English, Chinese